The ability to analyze nanoparticles in the atom probe has often been limited by the complexity of the sample preparation. In this work, we present a method to lift–out single nanoparticles in the scanning electron microscope. First, nanoparticles are dispersed on a lacey carbon grid, then positioned on a sharp substrate tip and coated on all sides with a metallic matrix by physical vapor deposition. Compositional and structural insights are provided for spherical gold nanoparticles and a segregation of silver and copper in silver copper oxide nanorods is shown in 3D atom maps. Using the standard atom probe reconstruction algorithm, data quality is limited by typical standard reconstruction artifacts for heterogeneous specimens (trajectory aberrations) and the choice of suitable coatings for the particles. This approach can be applied to various unsupported free-standing nanoparticles, enables preselection of particles via correlative techniques, and reliably produces well-defined structured samples. The only prerequisite is that the nanoparticles must be large enough to be manipulated, which was done for sizes down to ~50 nm.

This paper presents research work which crosses the divide between “Path Planning” and “Trajectory Generation & Tracking”. These subjects have tended to develop along two parallel lines, in isolation from each other. The work uses the Lagrange formulation for the three major joints of an industrial manipulator. Simple planning rules are developed from this formulation. The rules are used to select new paths for a manipulator rather than to improve preplanned trajectories. The method has been applied to pick and place tasks requiring gross motions of the manipulator and the results are presented. It is shown that using this method, pre-planned manipulator paths can be modified to improve the gross motions associated with the pick and place task.